Foundations of PLS-SEM Using SmartPLS

Course Language: English!

This two-day online course introduces participants to the state-of-the-art of partial least squares structural equation modeling (PLS-SEM) using the SmartPLS 3 software. The first day of the course provides a profound introduction to PLS-SEM. Participants will learn the foundations of PLS-SEM and how to apply it by means of the SmartPLS 3 software. The second day will cover the appropriate evaluation of the measurement and structural model including recent developments in model evaluation. The instructors will make use of several examples and hands-on exercises using the SmartPLS 3 software. 

PLS-SEM is a composite-based approach to SEM, which aims at maximizing the explained variance of dependent constructs in the path model. Compared to other SEM techniques, PLS-SEM allows researchers to estimate very complex models with many constructs and indicator variables. Furthermore, PLS-SEM allows to estimate reflective and formative constructs and generally offers much flexibility in terms of data requirements.

PLS-SEM has recently received considerable attention in a variety of disciplines, including

• marketing (Hair et al 2011, according to Google scholar the most-cited article ever published in Journal of Marketing Theory and Practice; Hair et al. 2012a, according to Google scholar the most-cited Journal of the Academy of Marketing Science article since 2012),
• strategic management (Hair et al. 2012b, according to Google scholar the most-cited Long Range Planning article since 2012),
• management information systems (Ringle et al. 2012, according to Google scholar the fifth-most cited MIS Quarterly article since 2012), and
• business administration in general (Sarstedt et al. 2016, according to Google scholar the second-most cited article published in the Journal of Business Research since 2016).

Also, several review studies across different disciplines substantiate that PLS-SEM has become a standard method in the multivariate analysis toolbox: e.g., Higher Education (Ghasemy et al. 2020), Human Resource Management (Ringle et al., 2018), Hospitality Research (Ali et al., 2018), Information Systems Research (Hair et al., 2017), Management Accounting (Nitzl, 2016), International Business (Richter et al., 2016), Tourism (do Valle and Assaker, 2016), Psychology (Willaby et al., 2015), Supply Chain Management (Kaufmann and Gaeckler, 2015), Family Business (Sarstedt et al., 2014), Operations Management (Peng and Lai, 2012), Strategic Management (Hair et al., 2012), Marketing (Hair et al., 2012), Management Information Systems (Ringle et al., 2012), Accounting (Lee et al., 2011), and International Marketing (Henseler et al., 2009).

Take a look at recent PLS-SEM publications!

This course has been designed to familiarize participants with the potentials of using the multivariate analysis method PLS-SEM in their research. The objectives of this course are to provide (1) an in-depth methodological introduction into the PLS-SEM approach (the nature of causal modeling, analytical objectives, some statistics), (2) the evaluation of measurement results, and (3) the evaluation of the structural model results. More specifically, participants will understand the following topics:

• Model development and fundamentals of PLS-SEM and latent variable models
• PLS path model estimation including the weighted PLS (WPLS) and consistent PLS (PLSc)
• Assessment and reporting of measurement and structural model results including Bootstrapping
• Prediction-oriented results analysis including PLSpredict
• New criteria for model assessment such as HTMT for discriminant validity, goodness of fit (e.g., SRMR), and model comparison & model selection

This course has been designed for full-time faculty and PhD students who are interested in learning how to use the PLS-SEM method in their own research applications. Basic knowledge of multivariate statistics and SEM techniques is helpful, but not required.

Participants will receive a certificate of attendance. Universities and academic institutions usually acknowledge this course with a workload of 3 ECTS.

• The course is based on the PLS-SEM textbook:

Hair, J. F., Hult, G. T. M., Ringle, C. M., and Sarstedt, M. 2017. A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). 2nd edition. Thousand Oaks, CA: Sage.

• Presentations: The session will cover theory and its application.
   
• Computer exercises using the latest SmartPLS 3 version: Specifically, theoretical explanations underlying the software procedures and practical exercises where participants will apply their learning to real-world examples provided by the instructor.

Course participants will receive a 90-days fully functional version of the software SmartPLS 3.